Classifier Visualisation
I developed an intuitive Python tool to train, evaluate, and visualize decision boundaries of multiple classifiers (SVM, Random Forest, Logistic Regression) on 2D datasets. I also implemented hyperparameter tuning to optimize model performance while providing visual explanations of model behavior and trade-offs.
K-nearest neighbors classifier fitted on a 2D dataset.
Optimising the regularization parameter of the Support Vector Classifier.